Dimensional Measurement Uncertainty and Inspection Planning

小行星9622692 现代加工设备可以生产具有复杂和精确几何形状的零件，但仍然需要高精度坐标测量机（CMM）来验证这些几何形状。 坐标测量机测量零件表面上的点的笛卡尔坐标，并使用最小最大或最小二乘法等标准将这些点拟合到标称零件几何形状。 这些方法产生相互矛盾或不一致的结果，因为测量不确定性尚未通过分析解决。 这项研究将开发的方法，涉及多元置信区间，点测量的最佳位置的一个功能，并以最大限度地提高信息含量的方式点的数量。 一个与工业界合作的实验项目将测试这些在处理CMM数据方面的进展。 这项研究影响了制造业的生产率和质量。 例如，该方法的一个应用是基于时间或成本约束来指定要在CMM上收集的点的数量，然后生成采样计划和测量特征的置信区域的估计。 或者，如果需要指定的准确度，则该方法可以提供用于进行测量的采样计划，并指定实现指定置信区域所需的点数。

9622692 Kurfess Modern machining facilities can produce parts with complex and precise geometry, but high precision coordinate measuring machines (CMMs) are still needed to validate these geometries. The CMMs measure Cartesian coordinates of points on the part surface, and these points are fit to nominal part geometries using criteria like mini-max or least squares. These methods yield conflicting or inconsistent results because measurement uncertainty has not been addressed by the analysis. This research will develop methods that relate multivariate confidence intervals, the optimal location of point measurements for a feature, and the number of points in a way that maximizes information content. An experimental program, in cooperation with industry, will test these advances in processing CMM data. This research impacts both productivity and quality in manufacture. For example, one application of this methodology is to specify the number of points to be collected on the CMM based on time or cost constraints, and then generate a sampling plan and an estimate of the confidence regions for the measured features. Alternatively, if a specified degree of accuracy is needed, then the methodology can provide a sampling plan for making measurements and specify the number of points needed to achieve a the specified confidence region.